Deep Fusion of Polystatic MIMO Radars with The Internet of Vehicles for Interference-free Environmental Perception

Abstract

This invention is related to a deep multi-sensor fusion system for inter-radar interference-free environmental perception comprising of (1) polystatic Multi-Input Multi-Output (MIMO) radars such as radio frequency radar and laser radar; (2) vehicle self-localization and navigation; (3) the Internet of Vehicles (IoV) including Vehicle-to-Vehicle communication (V2V), Vehicle-to-Infrastructure communication (V2I), other communication systems, data center / cloud; (4) passive sensors such as EOIR, and (5) deep multi-sensor fusion algorithms. The self-localization sensors and V2X formulate cooperative sensors. The polystatic MIMO radar on each vehicle utilizes both its own transmitted radar signals and ones from other vehicles to detect obstacles. The transmitted radar signals from other vehicles are not considered as interference or uselessness as conventional radars, but considered as useful signals to formulate a polystatic MIMO radar which can overcome the interference problem and improve the radar performance. This invention can be applied to all kinds of vehicles and robotics.

Description

TECHNICAL FIELD[0001]This invention relates to a deep fusion system of polystatic MIMO radars with the Internet of Vehicles (IoV), which can provide inter-radar interference-free environmental perception to enhance the vehicle safety.BACKGROUND OF THE INVENTION[0002]Advanced Driver Assistance Systems (ADAS) / self driving is one of the fastest-growing fields in automotive electronics. ADAS / self-driving is developed to improve the safety and efficiency of vehicle systems. There are mainly three approaches to implement ADAS / self-driving: (1) non-cooperative sensor fusion; (2) GPS navigation / vehicle-to-X networks used as cooperative sensors; (3) fusion of non-cooperative and cooperative sensors.[0003]More and more vehicles are being equipped with radar systems including radio frequency (RF) radar and laser radar (LIDAR) to provide various safety functions such as Adaptive Cruise Control (ACC), Forward Collision Warning (FCW), Automatic Emergency Braking (AEB), and Lane Departure Warning ...

AI Technical Summary

Benefits of technology

The patent text is about a technique called deep fusion that improves radar signal processing by using data from other sensors. This helps to reduce inter-radar interference and improves the performance of radar systems. The technique involves sharing data between vehicles and using the data from other sensors to process the radar signals. Overall, deep fusion helps to enhance the accuracy and efficiency of radar systems.

Problems solved by technology

Because of the big size and high price, LIDAR is less popular than RF radar in the present market.

This interference problem for both RF radar and LIDAR will become more and more severe because eventually every vehicle will be deployed with radars.

Because of the frequency band limit, the radar interference may be not overcome completely, especially for high-density traffic scenarios.

However, it will fail in detecting non-cooperative obstacles.

So navigation / V2X cannot be used alone for obstacle collision avoidance.

Conventional radar signal processing is difficult to mitigate inter-radar interference because the radar parameters and vehicle information are not shared between vehicles.

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